R

R. M. Barnett

Lawrence Berkeley National Laboratory

Publishes on Particle physics theoretical and experimental studies, High-Energy Particle Collisions Research, Particle Detector Development and Performance. 282 papers and 36.1k citations.

282Publications
36.1kTotal Citations

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Top publicationsby citations

Erratum: Review of Particle Properties
Ken‐ichi Hikasa, K. Hagiwara, S. Kawabata et al.|Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D. Particles and fields|1992
Cited by 34Open Access

ERRATA 8,=arg(gMigzt ) =@+ --mod2 (instead of N+ mode).As a consequence, the CP-violating asymmetry given by Eq. ( 26),( A ) = 15% cos8, +38% cos8z gE1 gM1 is (14.3+1.3)%, significantly larger than the result (3.8+1.4)%stated in the paper.

Calculation and Phenomenology of Two Body Decays of Neutralinos and Charginos to W, Z, and Higgs Bosons
John F. Gunion, Howard E. Haber, R. M. Barnett et al.|International Journal of Modern Physics A|1987
Cited by 25

We give explicit formulas for the decays of the neutralinos and charginos of the minimal model of supersymmetry into other neutralinos and charginos plus a W, Z, or Higgs boson. The important features of these decays are illustrated and their phenomenological implications discussed. In general, this class of two-body decays is dominant for the heaviest charginos and neutralinos.

The Projection-Pursuit Multivariate Transform for Improved Continuous Variable Modeling
Cited by 23

Summary Reservoir process-performance evaluation requires the simulation of multiple continuous variables such as porosity, water saturation, and permeability. Geostatistical realizations should reproduce the univariate and multivariate statistics that are deemed representative of the reservoir. A conventional work flow that sequentially applies cosimulation and cloud transformations is frequently used for this multivariate simulation. Although it effectively reproduces univariate properties, a common issue with this work flow is its inability to reproduce all the multivariate relationships that exist between variables. To resolve this issue, the projection-pursuit multivariate transform (PPMT) is applied to reservoir modeling. The PPMT work flow requires fewer steps, no manual tuning, and fewer assumptions than the conventional work flow. Background, essential steps, and practical considerations of the conventional and PPMT work flows are outlined before comparing them in a case study. The PPMT is shown to yield multivariate reproduction that is expected to improve reservoir forecasting.